TY - GEN
T1 - Hardware Implementation of Karnik-Mendel Algorithm for Interval Type-2 Fuzzy Sets and Systems
AU - Yáñez, Omar Hernández
AU - Lozano, Herón Molina
AU - Batyrshin, Ildar
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - The trend to accelerate the learning process in neural and fuzzy systems has led to the design of hardware implementations of different types of algorithms. In this paper we explore type-2 fuzzy logic systems acceleration, which can be applied to fuzzy logic control methods, signal processing, etc. Due to the three dimensional membership functions in the input of the system, different algorithms for the output processing stage have been developed. In order to have a fast response in type-2 fuzzy logic systems, in this paper we explore the Karnik-Mendel algorithms (KM), which are used to calculate the centroid at the output processing stage of the interval type-2 fuzzy system, through the application of iterative procedures. Because of the computation complexity of the iterative process, we propose a Hardware implementation of the KM algorithm using a High Level Synthesis tool, making possible to explore different types of implementation in order to obtain a significant reduction in computation time, and a reduction in hardware resources.
AB - The trend to accelerate the learning process in neural and fuzzy systems has led to the design of hardware implementations of different types of algorithms. In this paper we explore type-2 fuzzy logic systems acceleration, which can be applied to fuzzy logic control methods, signal processing, etc. Due to the three dimensional membership functions in the input of the system, different algorithms for the output processing stage have been developed. In order to have a fast response in type-2 fuzzy logic systems, in this paper we explore the Karnik-Mendel algorithms (KM), which are used to calculate the centroid at the output processing stage of the interval type-2 fuzzy system, through the application of iterative procedures. Because of the computation complexity of the iterative process, we propose a Hardware implementation of the KM algorithm using a High Level Synthesis tool, making possible to explore different types of implementation in order to obtain a significant reduction in computation time, and a reduction in hardware resources.
KW - FPGA
KW - High Level Synthesis
KW - Interval type-2 fuzzy systems
KW - Karnik-Mendel
UR - http://www.scopus.com/inward/record.url?scp=85075693403&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-33749-0_43
DO - 10.1007/978-3-030-33749-0_43
M3 - Contribución a la conferencia
SN - 9783030337483
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 537
EP - 545
BT - Advances in Soft Computing - 18th Mexican International Conference on Artificial Intelligence, MICAI 2019, Proceedings
A2 - Martínez-Villaseñor, Lourdes
A2 - Batyrshin, Ildar
A2 - Marín-Hernández, Antonio
PB - Springer
T2 - 18th Mexican International Conference on Artificial Intelligence, MICAI 2019
Y2 - 27 October 2019 through 2 November 2019
ER -